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ci/shard-test-api
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pdf
| Author | SHA1 | Date | |
|---|---|---|---|
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79f683cdf9 | ||
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ce74b1fc56 |
@@ -272,6 +272,8 @@ ENV_FILE_STORAGE_AZURE_CONTAINER = "HINDSIGHT_API_FILE_STORAGE_AZURE_CONTAINER"
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ENV_FILE_STORAGE_AZURE_ACCOUNT_NAME = "HINDSIGHT_API_FILE_STORAGE_AZURE_ACCOUNT_NAME"
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ENV_FILE_STORAGE_AZURE_ACCOUNT_KEY = "HINDSIGHT_API_FILE_STORAGE_AZURE_ACCOUNT_KEY"
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ENV_FILE_PARSER = "HINDSIGHT_API_FILE_PARSER"
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ENV_FILE_PARSER_IRIS_TOKEN = "HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN"
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ENV_FILE_PARSER_IRIS_ORG_ID = "HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID"
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ENV_FILE_CONVERSION_MAX_BATCH_SIZE_MB = "HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE_MB"
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ENV_FILE_CONVERSION_MAX_BATCH_SIZE = "HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE"
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ENV_ENABLE_FILE_UPLOAD_API = "HINDSIGHT_API_ENABLE_FILE_UPLOAD_API"
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@@ -645,7 +647,9 @@ class HindsightConfig:
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file_storage_azure_container: str | None # Azure container name (required for azure storage)
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file_storage_azure_account_name: str | None # Azure storage account name
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file_storage_azure_account_key: str | None # Azure storage account key
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file_parser: str # File parser to use (e.g., "markitdown")
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file_parser: str # File parser to use (e.g., "markitdown", "iris")
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file_parser_iris_token: str | None # Vectorize API token for iris parser (VECTORIZE_TOKEN)
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file_parser_iris_org_id: str | None # Vectorize org ID for iris parser (VECTORIZE_ORG_ID)
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file_conversion_max_batch_size_mb: int # Max total batch size in MB (all files combined)
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file_conversion_max_batch_size: int # Max files per request
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enable_file_upload_api: bool
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@@ -712,6 +716,8 @@ class HindsightConfig:
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"file_storage_s3_secret_access_key",
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"file_storage_gcs_service_account_key",
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"file_storage_azure_account_key",
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# File parser credentials
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"file_parser_iris_token",
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}
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# CONFIGURABLE_FIELDS: Safe behavioral settings that can be customized per-tenant/bank
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@@ -1030,6 +1036,8 @@ class HindsightConfig:
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file_storage_azure_account_name=os.getenv(ENV_FILE_STORAGE_AZURE_ACCOUNT_NAME) or None,
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file_storage_azure_account_key=os.getenv(ENV_FILE_STORAGE_AZURE_ACCOUNT_KEY) or None,
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file_parser=os.getenv(ENV_FILE_PARSER, DEFAULT_FILE_PARSER),
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file_parser_iris_token=os.getenv(ENV_FILE_PARSER_IRIS_TOKEN) or None,
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file_parser_iris_org_id=os.getenv(ENV_FILE_PARSER_IRIS_ORG_ID) or None,
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file_conversion_max_batch_size_mb=int(
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os.getenv(ENV_FILE_CONVERSION_MAX_BATCH_SIZE_MB, str(DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE_MB))
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),
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@@ -1374,7 +1374,7 @@ class MemoryEngine(MemoryEngineInterface):
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logger.debug(f"File storage initialized ({config.file_storage_type})")
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# Initialize parser registry
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from .parsers import FileParserRegistry, MarkitdownParser
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from .parsers import FileParserRegistry, IrisParser, MarkitdownParser
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self._parser_registry = FileParserRegistry()
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try:
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@@ -1382,6 +1382,13 @@ class MemoryEngine(MemoryEngineInterface):
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logger.debug("Registered markitdown parser")
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except ImportError:
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logger.warning("markitdown not available - file parsing disabled")
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iris_token = config.file_parser_iris_token
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iris_org_id = config.file_parser_iris_org_id
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if iris_token and iris_org_id:
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self._parser_registry.register(IrisParser(token=iris_token, org_id=iris_org_id))
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logger.debug("Registered iris parser")
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else:
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logger.debug("Iris parser not registered (VECTORIZE_TOKEN or VECTORIZE_ORG_ID not set)")
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# Set executor for task backend and initialize
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self._task_backend.set_executor(self.execute_task)
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@@ -1,9 +1,10 @@
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"""File parser implementations."""
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from .base import FileParser
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from .base import FileParser, UnsupportedFileTypeError
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from .iris import IrisParser
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from .markitdown import MarkitdownParser
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__all__ = ["FileParser", "MarkitdownParser", "FileParserRegistry"]
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__all__ = ["FileParser", "UnsupportedFileTypeError", "IrisParser", "MarkitdownParser", "FileParserRegistry"]
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class FileParserRegistry:
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@@ -43,7 +44,8 @@ class FileParserRegistry:
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ValueError: If no suitable parser found
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"""
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if name:
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# Explicit parser requested
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# Explicit parser requested — return it directly, let the parser
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# raise UnsupportedFileTypeError from convert() if needed
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if name not in self._parsers:
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raise ValueError(f"Parser '{name}' not found. Available: {list(self._parsers.keys())}")
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return self._parsers[name]
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@@ -3,6 +3,12 @@
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from abc import ABC, abstractmethod
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class UnsupportedFileTypeError(Exception):
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"""Raised by a parser when it does not support the given file type."""
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pass
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class FileParser(ABC):
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"""Abstract base for file to markdown parsers."""
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@@ -19,24 +25,27 @@ class FileParser(ABC):
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Markdown content as string
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Raises:
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ValueError: If file format is not supported
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RuntimeError: If parsing fails
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UnsupportedFileTypeError: If the file type is not supported by this parser
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RuntimeError: If parsing fails for another reason
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"""
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pass
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@abstractmethod
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def supports(self, filename: str, content_type: str | None = None) -> bool:
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"""
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Check if parser supports this file type.
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Override this for local/static extension-based filtering.
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Parsers that delegate to a remote service should leave this as True
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and raise UnsupportedFileTypeError from convert() instead.
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Args:
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filename: File name (used for extension check)
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content_type: MIME type (optional)
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Returns:
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True if this parser can handle the file
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True if this parser can handle the file (default: True)
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"""
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pass
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return True
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@abstractmethod
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def name(self) -> str:
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@@ -0,0 +1,137 @@
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"""Iris parser implementation using the Vectorize Iris HTTP API."""
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import asyncio
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import logging
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import mimetypes
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import time
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import httpx
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from .base import FileParser, UnsupportedFileTypeError
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logger = logging.getLogger(__name__)
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_IRIS_BASE_URL = "https://api.vectorize.io/v1"
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_DEFAULT_POLL_INTERVAL = 2.0 # seconds
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_DEFAULT_TIMEOUT = 300.0 # seconds
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class IrisParser(FileParser):
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"""
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Iris file parser using the Vectorize Iris cloud extraction service.
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Uploads files to the Vectorize Iris API, starts an extraction job,
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and polls until the text is ready. The API determines which file types
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are supported — UnsupportedFileTypeError is raised if the file is rejected.
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Authentication:
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Requires HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN and
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HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID environment variables,
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or pass them explicitly via the constructor.
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"""
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def __init__(
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self,
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token: str,
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org_id: str,
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poll_interval: float = _DEFAULT_POLL_INTERVAL,
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timeout: float = _DEFAULT_TIMEOUT,
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):
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"""
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Initialize iris parser.
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Args:
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token: Vectorize API token
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org_id: Vectorize organization ID
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poll_interval: Seconds between status poll requests (default: 2)
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timeout: Maximum seconds to wait for extraction (default: 300)
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"""
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self._token = token
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self._org_id = org_id
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self._poll_interval = poll_interval
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self._timeout = timeout
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self._auth_headers = {"Authorization": f"Bearer {token}"}
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async def convert(self, file_data: bytes, filename: str) -> str:
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"""
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Parse file to text using the Vectorize Iris API.
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Raises:
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UnsupportedFileTypeError: If the Iris API rejects the file type (4xx)
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RuntimeError: If extraction fails for another reason
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"""
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content_type = mimetypes.guess_type(filename)[0] or "application/octet-stream"
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async with httpx.AsyncClient() as client:
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# Step 1: Request a presigned upload URL
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init_resp = await client.post(
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f"{_IRIS_BASE_URL}/org/{self._org_id}/files",
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headers=self._auth_headers,
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json={"name": filename, "contentType": content_type},
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)
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_raise_for_status(init_resp, filename, "file upload init")
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init_data = init_resp.json()
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file_id: str = init_data["fileId"]
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upload_url: str = init_data["uploadUrl"]
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# Step 2: Upload the file bytes to the presigned URL (no auth header)
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upload_resp = await client.put(
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upload_url,
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content=file_data,
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headers={"Content-Type": content_type},
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)
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_raise_for_status(upload_resp, filename, "file upload")
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# Step 3: Start extraction
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extract_resp = await client.post(
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f"{_IRIS_BASE_URL}/org/{self._org_id}/extraction",
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headers=self._auth_headers,
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json={"fileId": file_id},
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)
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_raise_for_status(extract_resp, filename, "start extraction")
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extraction_id: str = extract_resp.json()["extractionId"]
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# Step 4: Poll until ready or timeout
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deadline = time.monotonic() + self._timeout
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while True:
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status_resp = await client.get(
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f"{_IRIS_BASE_URL}/org/{self._org_id}/extraction/{extraction_id}",
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headers=self._auth_headers,
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)
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_raise_for_status(status_resp, filename, "poll extraction status")
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status_data = status_resp.json()
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if status_data.get("ready"):
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data = status_data.get("data", {})
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if not data.get("success"):
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error = data.get("error", "unknown error")
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raise RuntimeError(f"Iris extraction failed for '{filename}': {error}")
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text = data.get("text")
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if not text:
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raise RuntimeError(f"No content extracted from '{filename}'")
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return text
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if time.monotonic() >= deadline:
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raise RuntimeError(f"Iris extraction timed out after {self._timeout}s for '{filename}'")
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await asyncio.sleep(self._poll_interval)
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def name(self) -> str:
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"""Get parser name."""
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return "iris"
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def _raise_for_status(response: httpx.Response, filename: str, step: str) -> None:
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"""
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Raise an appropriate error including the response body on HTTP errors.
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Raises UnsupportedFileTypeError for 4xx responses (file rejected by the API),
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RuntimeError for other HTTP errors.
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"""
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if not response.is_error:
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return
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body = response.text or "<empty>"
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msg = f"Iris API error during {step} for '{filename}': {response.status_code} {response.reason_phrase} — {body}"
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if response.is_client_error:
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raise UnsupportedFileTypeError(msg)
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raise RuntimeError(msg)
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@@ -262,6 +262,8 @@ def main():
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file_storage_azure_account_name=config.file_storage_azure_account_name,
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file_storage_azure_account_key=config.file_storage_azure_account_key,
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file_parser=config.file_parser,
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file_parser_iris_token=config.file_parser_iris_token,
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file_parser_iris_org_id=config.file_parser_iris_org_id,
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file_conversion_max_batch_size_mb=config.file_conversion_max_batch_size_mb,
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file_conversion_max_batch_size=config.file_conversion_max_batch_size,
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enable_file_upload_api=config.enable_file_upload_api,
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@@ -0,0 +1,72 @@
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"""
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Integration tests for the Iris file parser.
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Tests are skipped automatically if HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN
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and HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID are not set in the environment.
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"""
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import os
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import pytest
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from hindsight_api.config import ENV_FILE_PARSER_IRIS_ORG_ID, ENV_FILE_PARSER_IRIS_TOKEN
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from hindsight_api.engine.parsers.iris import IrisParser
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_token = os.getenv(ENV_FILE_PARSER_IRIS_TOKEN)
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_org_id = os.getenv(ENV_FILE_PARSER_IRIS_ORG_ID)
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pytestmark = pytest.mark.skipif(
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not (_token and _org_id),
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reason="HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN and HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID not set",
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)
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# Minimal valid PDF with the text "Hello from Hindsight"
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_SAMPLE_PDF = b"""%PDF-1.4
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1 0 obj
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<< /Type /Catalog /Pages 2 0 R >>
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endobj
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2 0 obj
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<< /Type /Pages /Kids [3 0 R] /Count 1 >>
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endobj
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3 0 obj
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<< /Type /Page /Parent 2 0 R /MediaBox [0 0 612 792]
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/Contents 4 0 R /Resources << /Font << /F1 << /Type /Font /Subtype /Type1 /BaseFont /Helvetica >> >> >> >>
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endobj
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4 0 obj
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<< /Length 44 >>
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stream
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BT /F1 12 Tf 100 700 Td (Hello from Hindsight) Tj ET
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endstream
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endobj
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xref
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0 5
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0000000000 65535 f
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0000000009 00000 n
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0000000058 00000 n
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0000000115 00000 n
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0000000274 00000 n
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trailer << /Size 5 /Root 1 0 R >>
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startxref
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369
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%%EOF"""
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@pytest.fixture
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def iris_parser() -> IrisParser:
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return IrisParser(token=_token, org_id=_org_id)
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@pytest.mark.asyncio
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async def test_iris_parser_converts_pdf(iris_parser: IrisParser):
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"""IrisParser should extract text from a valid PDF."""
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result = await iris_parser.convert(_SAMPLE_PDF, "sample.pdf")
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assert isinstance(result, str)
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assert len(result) > 0
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@pytest.mark.asyncio
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async def test_iris_parser_name(iris_parser: IrisParser):
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"""IrisParser.name() should return 'iris'."""
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assert iris_parser.name() == "iris"
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@@ -636,12 +636,34 @@ Configuration for the file upload and conversion pipeline (used by `POST /v1/def
|
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| Variable | Description | Default |
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|----------|-------------|---------|
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| `HINDSIGHT_API_ENABLE_FILE_UPLOAD_API` | Enable the file upload API endpoint | `true` |
|
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| `HINDSIGHT_API_FILE_PARSER` | File parser to use (`markitdown`) | `markitdown` |
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| `HINDSIGHT_API_FILE_PARSER` | File parser to use (`markitdown`, `iris`) | `markitdown` |
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| `HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE` | Max files per upload request | `10` |
|
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| `HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE_MB` | Max total upload size per request (MB) | `100` |
|
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| `HINDSIGHT_API_FILE_DELETE_AFTER_RETAIN` | Delete stored files after memory extraction completes | `true` |
|
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|
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**Supported formats (via markitdown):** PDF, DOCX, DOC, PPTX, PPT, XLSX, XLS, images (JPG, PNG, GIF — OCR), audio (MP3, WAV — transcription), HTML, TXT, MD, CSV, and more.
|
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#### Parser: markitdown (default)
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|
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Local file-to-markdown conversion using [Microsoft's markitdown](https://github.com/microsoft/markitdown). No external service required.
|
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|
||||
**Supported formats:** PDF, DOCX, DOC, PPTX, PPT, XLSX, XLS, images (JPG, PNG — OCR), audio (MP3, WAV — transcription), HTML, TXT, MD, CSV.
|
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|
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#### Parser: iris
|
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|
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Cloud-based extraction via [Vectorize Iris](https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/). Higher quality extraction for complex documents, powered by a remote AI service.
|
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|
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| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN` | Vectorize API token | — |
|
||||
| `HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID` | Vectorize organization ID | — |
|
||||
|
||||
**Supported formats:** PDF, DOCX, DOC, PPTX, PPT, XLSX, XLS, images (JPG, JPEG, PNG, GIF, BMP, TIFF, WEBP), HTML, TXT, MD, CSV.
|
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|
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```bash
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# Use iris parser (requires Vectorize account)
|
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export HINDSIGHT_API_FILE_PARSER=iris
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export HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN=your-vectorize-token
|
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export HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID=your-org-id
|
||||
```
|
||||
|
||||
```bash
|
||||
# Increase batch limits for large file imports
|
||||
|
||||
Reference in New Issue
Block a user